Evolvement of Excusable Delay Clauses in Government Contracts since the COVID-19 Pandemic
Bibliographic record
Abstract
Excusable delay clauses in government construction contracts, often considered boilerplate with minimal modifications, have increased in attention since the outbreak of COVID-19. Despite the studies enumerating triggering events of the clause in the background of the pandemic, it is necessary to capture insights into how the unprecedented event is systematically accommodated by contract languages. The overarching goal of this study is to identify changes in contract languages over the pre-and post-pandemic eras by state departments of transportation (DOTs), focusing on excusable delay clauses. This study conducts a content analysis and a comparative analysis of state DOT construction contract documents, including requests for proposals and agreements. Longitudinally, the study analyzes changes within a state DOT over the pre-and postpandemic eras. Cross-sectionally, the study compares the similarities and differences in the changes across different state DOTs. The results show that many DOTs specify a list of events that trigger the excusable delay clauses in the postpandemic era. The study also identifies example languages, such as quarantine restrictions and material escalations, that have been added in the postpandemic era. This study contributes to understanding how excusable delay contract languages have changed pre- and post-COVID-19 and the events that trigger such clauses in government construction projects. The findings are anticipated to benefit practitioners, especially those in the US transportation infrastructure industry and other common law authorities, by benchmarking necessary contract clause changes about the pandemic and unprecedented future events alike.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".